Steven W. Wingett

Mapping long-range promoter contacts in human cells with high-resolution capture Hi-C

Transcriptional control in large genomes often requires looping interactions between distal DNA elements, such as enhancers and target promoters. Current chromosome conformation capture techniques do not offer sufficiently high resolution to interrogate these regulatory interactions on a genomic scale. Here we use Capture Hi-C (CHi-C), an adapted genome conformation assay, to examine the long-range interactions of almost 22,000 promoters in 2 human blood cell types. We identify over 1.6 million shared and cell type–restricted interactions spanning hundreds of kilobases between promoters and distal loci. Transcriptionally active genes contact enhancer-like elements, whereas transcriptionally inactive genes interact with previously uncharacterized elements marked by repressive features that may act as long-range silencers. Finally, we show that interacting loci are enriched for disease-associated SNPs, suggesting how distal mutations may disrupt the regulation of relevant genes. This study provides new insights and accessible tools to dissect the regulatory interactions that underlie normal and aberrant gene regulation.

Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters

Summary Long-range interactions between regulatory elements and gene promoters play key roles in transcriptional regulation. The vast majority of interactions are uncharted, constituting a major missing link in understanding genome control. Here, we use promoter capture Hi-C to identify interacting regions of 31,253 promoters in 17 human primary hematopoietic cell types. We show that promoter interactions are highly cell type specific and enriched for links between active promoters and epigenetically marked enhancers. Promoter interactomes reflect lineage relationships of the hematopoietic tree, consistent with dynamic remodeling of nuclear architecture during differentiation. Interacting regions are enriched in genetic variants linked with altered expression of genes they contact, highlighting their functional role. We exploit this rich resource to connect non-coding disease variants to putative target promoters, prioritizing thousands of disease-candidate genes and implicating disease pathways. Our results demonstrate the power of primary cell promoter interactomes to reveal insights into genomic regulatory mechanisms underlying common diseases.

The pluripotent regulatory circuitry connecting promoters to their long-range interacting elements

The mammalian genome harbors up to one million regulatory elements often located at great distances from their target genes. Long-range elements control genes through physical contact with promoters and can be recognized by the presence of specific histone modifications and transcription factor binding. Linking regulatory elements to specific promoters genome-wide is currently impeded by the limited resolution of high-throughput chromatin interaction assays. Here we apply a sequence capture approach to enrich Hi-C libraries for >22,000 annotated mouse promoters to identify statistically significant, long-range interactions at restriction fragment resolution, assigning long-range interacting elements to their target genes genome-wide in embryonic stem cells and fetal liver cells. The distal sites contacting active genes are enriched in active histone modifications and transcription factor occupancy, whereas inactive genes contact distal sites with repressive histone marks, demonstrating the regulatory potential of the distal elements identified. Furthermore, we find that coregulated genes cluster nonrandomly in spatial interaction networks correlated with their biological function and expression level. Interestingly, we find the strongest gene clustering in ES cells between transcription factor genes that control key developmental processes in embryogenesis. The results provide the first genome-wide catalog linking gene promoters to their long-range interacting elements and highlight the complex spatial regulatory circuitry controlling mammalian gene expression.

Polycomb repressive complex PRC1 spatially constrains the mouse embryonic stem cell genome.

The Polycomb repressive complexes PRC1 and PRC2 maintain embryonic stem cell (ESC) pluripotency by silencing lineage-specifying developmental regulator genes. Emerging evidence suggests that Polycomb complexes act through controlling spatial genome organization. We show that PRC1 functions as a master regulator of mouse ESC genome architecture by organizing genes in three-dimensional interaction networks. The strongest spatial network is composed of the four Hox gene clusters and early developmental transcription factor genes, the majority of which contact poised enhancers. Removal of Polycomb repression leads to disruption of promoter-promoter contacts in the Hox gene network. In contrast, promoter-enhancer contacts are maintained in the absence of Polycomb repression, with accompanying widespread acquisition of active chromatin signatures at network enhancers and pronounced transcriptional upregulation of network genes. Thus, PRC1 physically constrains developmental transcription factor genes and their enhancers in a silenced but poised spatial network. We propose that the selective release of genes from this spatial network underlies cell fate specification during early embryonic development.

Cell-cycle dynamics of chromosomal organization at single-cell resolution

Chromosomes in proliferating metazoan cells undergo marked structural metamorphoses every cell cycle, alternating between highly condensed mitotic structures that facilitate chromosome segregation, and decondensed interphase structures that accommodate transcription, gene silencing and DNA replication. Here we use single-cell Hi-C (high-resolution chromosome conformation capture) analysis to study chromosome conformations in thousands of individual cells, and discover a continuum of cis-interaction profiles that finely position individual cells along the cell cycle. We show that chromosomal compartments, topological-associated domains (TADs), contact insulation and long-range loops, all defined by bulk Hi-C maps, are governed by distinct cell-cycle dynamics. In particular, DNA replication correlates with a build-up of compartments and a reduction in TAD insulation, while loops are generally stable from G1 to S and G2 phase. Whole-genome three-dimensional structural models reveal a radial architecture of chromosomal compartments with distinct epigenomic signatures. Our single-cell data therefore allow re-interpretation of chromosome conformation maps through the prism of the cell cycle.

Global Reorganization of the Nuclear Landscape in Senescent Cells

Summary Cellular senescence has been implicated in tumor suppression, development, and aging and is accompanied by large-scale chromatin rearrangements, forming senescence-associated heterochromatic foci (SAHF). However, how the chromatin is reorganized during SAHF formation is poorly understood. Furthermore, heterochromatin formation in senescence appears to contrast with loss of heterochromatin in Hutchinson-Gilford progeria. We mapped architectural changes in genome organization in cellular senescence using Hi-C. Unexpectedly, we find a dramatic sequence- and lamin-dependent loss of local interactions in heterochromatin. This change in local connectivity resolves the paradox of opposing chromatin changes in senescence and progeria. In addition, we observe a senescence-specific spatial clustering of heterochromatic regions, suggesting a unique second step required for SAHF formation. Comparison of embryonic stem cells (ESCs), somatic cells, and senescent cells shows a unidirectional loss in local chromatin connectivity, suggesting that senescence is an endpoint of the continuous nuclear remodelling process during differentiation.

CHiCAGO: robust detection of DNA looping interactions in Capture Hi-C data

Capture Hi-C (CHi-C) is a method for profiling chromosomal interactions involving targeted regions of interest, such as gene promoters, globally and at high resolution. Signal detection in CHi-C data involves a number of statistical challenges that are not observed when using other Hi-C-like techniques. We present a background model and algorithms for normalisation and multiple testing that are specifically adapted to CHi-C experiments. We implement these procedures in CHiCAGO (http://regulatorygenomicsgroup.org/chicago), an open-source package for robust interaction detection in CHi-C. We validate CHiCAGO by showing that promoter-interacting regions detected with this method are enriched for regulatory features and disease-associated SNPs.

Comparison of Hi-C results using in-solution versus in-nucleus ligation.

BackgroundChromosome conformation capture and various derivative methods such as 4C, 5C and Hi-C have emerged as standard tools to analyze the three-dimensional organization of the genome in the nucleus. These methods employ ligation of diluted cross-linked chromatin complexes, intended to favor proximity-dependent, intra-complex ligation. During development of single-cell Hi-C, we devised an alternative Hi-C protocol with ligation in preserved nuclei rather than in solution. Here we directly compare Hi-C methods employing in-nucleus ligation with the standard in-solution ligation.ResultsWe show in-nucleus ligation results in consistently lower levels of inter-chromosomal contacts. Through chromatin mixing experiments we show that a significantly large fraction of inter-chromosomal contacts are the result of spurious ligation events formed during in-solution ligation. In-nucleus ligation significantly reduces this source of experimental noise, and results in improved reproducibility between replicates. We also find that in-nucleus ligation eliminates restriction fragment length bias found with in-solution ligation. These improvements result in greater reproducibility of long-range intra-chromosomal and inter-chromosomal contacts, as well as enhanced detection of structural features such as topologically associated domain boundaries.ConclusionsWe conclude that in-nucleus ligation captures chromatin interactions more consistently over a wider range of distances, and significantly reduces both experimental noise and bias. In-nucleus ligation creates higher quality Hi-C libraries while simplifying the experimental procedure. We suggest that the entire range of 3C applications are likely to show similar benefits from in-nucleus ligation.

HiCUP: pipeline for mapping and processing Hi-C data

HiCUP is a pipeline for processing sequence data generated by Hi-C and Capture Hi-C (CHi-C) experiments, which are techniques used to investigate three-dimensional genomic organisation. The pipeline maps data to a specified reference genome and removes artefacts that would otherwise hinder subsequent analysis. HiCUP also produces an easy-to-interpret yet detailed quality control (QC) report that assists in refining experimental protocols for future studies. The software is freely available and has already been used for processing Hi-C and CHi-C data in several recently published peer-reviewed studies.

Single-cell Hi-C for genome-wide detection of chromatin interactions that occur simultaneously in a single cell

Hi-C is a powerful method that provides pairwise information on genomic regions in spatial proximity in the nucleus. Hi-C requires millions of cells as input and, as genome organization varies from cell to cell, a limitation of Hi-C is that it only provides a population average of genome conformations. We developed single-cell Hi-C to create snapshots of thousands of chromatin interactions that occur simultaneously in a single cell. To adapt Hi-C to single-cell analysis, we modified the protocol to include in-nucleus ligation. This enables the isolation of single nuclei carrying Hi-C–ligated DNA into separate tubes, followed by reversal of cross-links, capture of biotinylated ligation junctions on streptavidin-coated magnetic beads and PCR amplification of single-cell Hi-C libraries. The entire laboratory protocol can be carried out in 1 week, and although we have demonstrated its use in mouse T helper (TH1) cells, it should be applicable to any cell type or species for which standard Hi-C has been successful. We also developed an analysis pipeline to filter noise and assess the quality of data sets in a few hours. Although the interactome maps produced by single-cell Hi-C are sparse, the data provide useful information to understand cellular variability in nuclear genome organization and chromosome structure. Standard wet and dry laboratory skills in molecular biology and computational analysis are required.